某地区某农产品收购量与年份YX196935.5819.6919557.965.33197031.0321.13195615.346.82197114.3332.34195713.558.17197213.8819.57195810.949.48197314.6616.3919596.398.03197419.3717.9619601.943.58197535.4718.3919610.061.17197635.4918.8319620.660.92197732.7721.1519636.041.63197832.219.8196415.417.73197938.534.86196515.39.46198053.7222.96196619.3213.97198151.317.45196735.7617.32198234.0416.05196835.0317.36198316.0317.38198421.7916.79第一步：描述统计量YXMean22.3585714.55500Median17.3650016.85500Maximum53.7200034.86000Minimum0.0600000.920000Std.Dev.14.957488.646472Skewness0.3249250.293930Kurtosis2.1447722.808145Jarque-Bera1.3460060.446120Probability0.5101740.800067Sum626.0400407.5400SumSq.Dev.6040.6062018.560Observations2828由表可知：y和x的最值，平均值，中位数，方差等数据。由经济理论知，农产品收购量受销售量影响，当销售量增加时，农产品收购量也会增加，它们之间有同步变动趋势，农产品收购量除受销售量的影响之外，还受到其他一些变量及随机因素的影响，将这些变量均归并到随机变量u中，根据X与Y的样本数据作散点图散点图由图可知，它们的变化趋势是线性的，由此建立农产品收购量与销售量之间的一元线性回归模型，通过Eviews一元线性回归模型参数DependentVariable:YMethod:LeastSquaresDate:06/10/12Time:16:31Sample:19551982Includedobservations:28VariableCoefficientStd.Errort-StatisticProb.C4.8570824.1098471.1818160.2480X1.2024380.2439014.9300350.0000R-squared0.483155Meandependentvar22.35857AdjustedR-squared0.463277S.D.dependentvar14.95748S.E.ofregression10.95806Akaikeinfocriterion7.694777Sumsquaredresid3122.055Schwarzcriterion7.789934Loglikelihood-105.7269Hannan-Quinncriter.7.723867F-statistic24.30524Durbin-Watsonstat0.964078Prob(F-statistic)0.000040一、即样本回归方程为在显著水平为0.05的条件下，查自由度为28-2=26的t分布，得临界值2.06，两参数的t值分别为1.181816,4.930035，故回归系数均显著不为零，回归模型中应包含常数项，X对Y有显著影响。二、通过White检验该模型中随机误差项是否存在异方差HeteroskedasticityTest:WhiteF-statistic4.502771Prob.F(2,25)0.0214Obs*R-squared7.415120Prob.Chi-Square(2)0.0245ScaledexplainedSS10.42735Prob.Chi-Square(2)0.0054TestEquation:DependentVariable:RESID^2Method:LeastSquaresDate:06/10/12Time:16:39Sample:19551982Includedobservations:28VariableCoefficientStd.Errort-StatisticProb.C8.50754993.962200.0905420.9286X-0.06378212.23389-0.0052140.9959X^20.3660030.3650621.0025780.3257R-squar